This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...
Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
Scientists have long relied on abstract models to study phenomena that are too complex for direct observation and experimentation. As new scientific modeling methodologies emerge...
Using a single traditional gang scheduling algorithm cannot provide the best performance for all workloads and parallel architectures. A solution for this problem is the use of...
We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...